Information processing apparatus and non-transitory computer-readable recording medium

ABSTRACT

An information processing apparatus includes an acquisition unit configured to acquire at least one of weather information and time information of a predetermined area as an environmental parameter, a use history unit configured to acquire a use history including a use section, a use time, and vehicle information of a vehicle previously used by a user, a prediction unit configured to perform a demand prediction of a vehicle to be used by the user based on correspondence information with the environmental parameter and the use history stored in association with each other, and a vehicle arrangement plan output unit configured to output a plan of arrangement locations of the vehicles planed based on the demand prediction of the vehicle performed by the demand prediction unit.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 16/359,653 filed Mar. 20, 2019, which claimspriority to Japanese Patent Application No. 2018-054960 filed on Mar.22, 2018, which are incorporated herein by reference in its entiretyincluding the specification, drawings and abstract.

BACKGROUND 1. Technical Field

The present disclosure relates to an information processing apparatusand a non-transitory computer-readable recording medium storing aninformation processing program.

2. Description of Related Art

A car sharing system in which a plurality of users shares one vehiclehas become widespread. The car sharing system is different from a carrental service of the related art in that a vehicle can be used for ashorter term.

When a car sharing system business is newly started, the scale of thesystem needs to be decided in consideration of feasibility. From aviewpoint of meeting users' demand, it is desirable to increase thenumber of vehicles usable as a shared vehicle. However, an increase inthe number of shared vehicles results in an increase in supply andmaintenance costs of a parking space at a station, in addition to anincrease in supply and maintenance costs of vehicles, causingdeterioration of feasibility. Accordingly, it is desirable to achieveimprovement of availability of vehicles usable as a shared vehicle suchthat user's demand is met as much as possible and profit can be ensured.

For example, in a car sharing system of Japanese Unexamined PatentApplication Publication No. 2016-095750 (JP 2016-095750 A), a techniquefor relaxing uneven distribution of vehicles due to concentration ofuser's use at a specific station is disclosed. Specifically, a degree ofuneven distribution indicating strength of uneven distribution ofvehicles in a predetermined area is calculated based on a distributionof vehicles that are on standby in a usable state at each station, andwhen the calculated degree of uneven distribution is equal to or greaterthan a predetermined threshold, processing for decreasing the degree ofuneven distribution is executed.

SUMMARY

The processing for decreasing the degree of uneven distribution isexecuted as described in JP 2016-095750 A, whereby it is possible torelax uneven distribution of vehicles due to concentration of user's useat the specific station to a certain degree. However, with stopgapprocessing for decreasing the degree of uneven distribution of vehiclesafter occurrence of a situation in which the vehicles are unevenlydistributed at the specific station, it may not be possible tosufficiently decrease the degree of uneven distribution depending on themagnitude of the degree of uneven distribution. Specifically, as theprocessing for decreasing the degree of uneven distribution in JP2016-095750 A, processing for forwarding, to another station, a vehiclethat is on standby at a usable station has been suggested; however, forexample, when the number of vehicles that are on standby at the usablestation is small in a time period during which use reservations for avehicle of the users increases, there is a possibility of beingincapable of coping with the situation through the forwarding processingdescribed above. In this way, in the related art, a countermeasure fordecreasing the degree of uneven distribution of the vehicles isimplemented; however, a problem relating to uneven distribution ofvehicles remains, and it is desirable to construct a car sharing systemcapable of renting vehicles to more users.

The disclosure provides an information processing apparatus and anon-transitory computer-readable recording medium storing an informationprocessing program capable of suppressing uneven distribution ofvehicles in a specific area and improving availability of vehiclesstored in a car sharing system.

A first aspect of the disclosure relates to an information processingapparatus. The information processing apparatus includes anenvironmental parameter acquisition unit, a use history unit, a demandprediction unit, and a vehicle arrangement plan output unit. Theenvironmental parameter acquisition unit is configured to acquire atleast one of weather information and time information of a predeterminedarea as an environmental parameter. The use history unit is configuredto acquire a use history including a use section, a use time, andvehicle information of a vehicle previously used by a user. The demandprediction unit is configured to perform a demand prediction of avehicle to be used by the user based on correspondence information withthe environmental parameter and the use history stored in associationwith each other. The vehicle arrangement plan output unit is configuredto output a plan of arrangement locations of the vehicles planed basedon the demand prediction of the vehicle performed by the demandprediction unit.

In the information processing apparatus according to the first aspect,the vehicle information may include a color, a vehicle type, and anaccessory of a vehicle. The demand prediction unit may be configured toperform a demand prediction of the vehicle to be used by the user foreach predetermined area. The vehicle corresponds to the vehicleinformation. The vehicle arrangement plan output unit may be configuredto output arrangement locations of vehicles corresponding to the vehicleinformation and the number of the vehicles for each predetermined areabased on the demand prediction of the vehicle corresponding to thevehicle information.

In the information processing apparatus according to the first aspect,the environmental parameter acquisition unit may be configured tofurther acquire a degree of congestion of a road in a predeterminedarea. The vehicle arrangement plan output unit may be configured tooutput the plan of the arrangement locations of the vehicles planedbased on the demand prediction of the vehicle performed by the demandprediction unit and the degree of congestion of the road.

The information processing apparatus according to the first aspect mayfurther include a reception unit and a traveling route decision unit.The reception unit may be configured to receive a use reservation of avehicle and store the use reservation in use reservation database. Thetraveling route decision unit may be configured to decide a travelingroute from a location where a vehicle determined as being usable basedon the use reservation is parked, toward an arrangement location of thevehicle output from the vehicle arrangement plan output unit.

The information processing apparatus according to the above-describedaspect may further include a notification unit and a controller. Thenotification unit may be configured to notify the autonomous drivingvehicle determined as being usable based on the use reservation, of thetraveling route decided by the traveling route decision unit. Thecontroller may be configured to control the vehicle notified by thenotification unit, to the arrangement location of the vehicle outputfrom the vehicle arrangement plan output unit along the traveling route.

A second aspect of the disclosure relates to a non-transitorycomputer-readable recording medium storing an information processingprogram. The information processing program causes a computer to executeacquiring at least one of weather information and time information as anenvironmental parameter, acquiring a use history including a usesection, a use time, and vehicle information of a vehicle previouslyused by a user, performing a demand prediction of a vehicle to be usedby the user based on correspondence information with the weatherinformation and the time information and the use history stored inassociation with each other, and outputting a plan of arrangementlocations of the vehicles planed based on the demand prediction of thevehicle.

According to the above-described aspects, it is possible to providearrangement of vehicles capable of suppressing uneven distribution ofvehicles in a specific area and improving availability of vehiclesstored in a car sharing system.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, advantages, and technical and industrial significance ofexemplary embodiments will be described below with reference to theaccompanying drawings, in which like numerals denote like elements, andwherein:

FIG. 1 is a diagram showing a configuration example of a car sharingsystem according to an embodiment;

FIG. 2 is a diagram showing an example of the functional blockconfiguration of an information processing apparatus;

FIG. 3 is a table showing a specific example of an environmentalparameter DB;

FIG. 4 is a table showing a specific example of a use reservation DB;

FIG. 5 is a table showing a specific example of a vehicle informationDB;

FIG. 6 is a flowchart showing an example of a processing procedure thatis executed by the information processing apparatus;

FIG. 7 is a flowchart showing an example of demand prediction processingshown in FIG. 6;

FIG. 8 is a table showing an example of correspondence information;

FIG. 9 is a diagram showing an example of a vehicle arrangement plan;and

FIG. 10 is a diagram showing another example of the vehicle arrangementplan.

DETAILED DESCRIPTION OF EMBODIMENTS

Embodiments will be described referring to the accompanying drawings. Inthe drawings, the same reference numerals have the same or similarconfigurations.

System Configuration

FIG. 1 is a diagram showing a configuration example of a car sharingsystem 1 according to an embodiment. The car sharing system 1 includesan information processing apparatus 10, user terminals 20, and vehicles30. In each of the vehicles 30, an in-vehicle device 30 a is mounted.The information processing apparatus 10, the user terminals 20, and thein-vehicle devices 30 a can perform communication with each otherthrough a communication network N.

The car sharing system 1 performs a demand prediction of a vehicle to beused by a user for each predetermined area based on correspondenceinformation with a predetermined environmental parameter and a usehistory relating to a vehicle of the user stored in association witheach other, and outputs an arrangement plan of vehicles based on thedemand prediction.

In general, sharing the same vehicle 30 among a plurality of users iscalled car sharing. The car sharing in the specification includes, forexample, round-trip in which the vehicle 30 needs to be returned to astation where the vehicle 30 is rented, and one-way in which a vehicleis permitted to be returned to a station other than a station where thevehicle is rented. The disclosure is not limited thereto, and any aspectin which the users share the same vehicle 30 is included in the carsharing in the specification.

The information processing apparatus 10 receives a use reservation forcar sharing from the user and registers the received use reservation ina database. A use history including a use section, a use time, andvehicle information (color, a vehicle type, an accessory, or the like ofthe vehicle) of the vehicle actually used by the user is also registeredin the database. The information processing apparatus 10 registers anenvironmental parameter including weather information and timeinformation of a predetermined area in the database. In the embodiment,a demand prediction of a vehicle to be used by the user is performedbased on the correspondence information with the above-describedenvironmental parameter and the use history stored in association witheach other, and the arrangement plan of the vehicles is output based onthe demand prediction of the vehicle. Details of the functions of theinformation processing apparatus 10 will be described below. Theinformation processing apparatus 10 may be constituted of one or aplurality of information processing apparatuses or may be constitutedusing a cloud server or a virtual server.

The user terminal 20 is a terminal that is used by a user who uses thecar sharing system 1, and is, for example, a smartphone, a tabletterminal, a mobile phone, a notebook personal computer, or the like. Inthe user terminal 20, a screen for reserving car sharing is displayed,and the user inputs various kinds of information (vehicle type, color,accessory, use section, use time, getting-in place, getting-off place,and the like) on the screen to make a use reservation for car sharing.

The vehicle 30 is a vehicle that is used by the user, and includes bothof a private automobile and an automobile owned by a company. Thevehicle 30 may be any vehicle as long as the vehicle is usable by theuser and is movable along a free traveling route. Specifically, avehicle 30 that a company rents for car sharing, a taxi, or a privatelyowned vehicle 30 may be used. The vehicle 30 is not limited to anautomobile, and may be, for example, a heavy vehicle 30, such as a bus,that ten-odd people to tens of people can get in or a motorcycle. Thevehicle 30 may be a vehicle 30 (hereinafter, referred to as a “manualdriving vehicle”) that the user drives while holding a steering wheel,or may be a vehicle 30 (hereinafter, referred to as an “autonomousdriving vehicle”) that can perform autonomous driving.

When the vehicle 30 is a manual driving vehicle, the in-vehicle device30 a may be a device (for example, a navigation device) that is able todisplay a traveling route to a destination notified from the informationprocessing apparatus 10. When the vehicle 30 is an autonomous drivingvehicle, the in-vehicle device 30 a performs various kinds of controlfor autonomously driving the vehicle 30 along the traveling route to thedestination transmitted from the information processing apparatus 10.

Functional Block Configuration

FIG. 2 is a diagram showing an example of the functional blockconfiguration of the information processing apparatus 10. Theinformation processing apparatus 10 includes a reception unit 101, anacquisition unit 102, a prediction unit 103 (demand prediction unit), avehicle arrangement plan output unit 104, a traveling route decisionunit 105, and a storage unit 110. In the embodiment, the informationprocessing apparatus 10 does not need to have all of the functions shownin FIG. 2, and may have at least a part of the functions shown in FIG.2. The information processing apparatus 10 may have functions other thanthe functions shown in FIG. 2.

The reception unit 101, the acquisition unit 102, the prediction unit103, the vehicle arrangement plan output unit 104, and the travelingroute decision unit 105 can be implemented by a central processing unit(CPU) of the information processing apparatus 10 executing a programstored in a memory. The program can be stored in a recording medium. Therecording medium storing the program may be a non-transitory recordingmedium. The non-transitory recording medium is not particularly limited,and may be, for example, a recording medium, such as a universal serialbus (USB) memory or a compact disc read only memory (CD-ROM). Thestorage unit 110 can be implemented using a memory or a storage devicein the information processing apparatus 10.

The storage unit 110 stores an environmental parameter database(hereinafter, referred to as an “environmental parameter DB”) 110 a, ause reservation database (hereinafter, referred to as a “use reservationDB”) 110 b, and a vehicle information database (hereinafter, referred toas a “vehicle information DB”) 110 c. In the environmental parameter DB110 a, information relating to weather information, map information,time information, traffic information (traffic condition of a road, suchas congestion) in a predetermined area is stored. In the use reservationDB 110 b, information relating to a use section, a use time, and vehicleinformation of a vehicle scheduled to be used by the user is storedcorresponding to information relating to the user who registers use inthe car sharing system 1. In the vehicle information DB 110 c,information relating to the vehicle 30 including various vehicle typesor colors, a location for storage of the vehicle 30 corresponding to theabove-described information, and the like are stored.

The reception unit 101 receives a use reservation for car sharingincluding the use section, the use time, and the vehicle information(color, vehicle type, accessory, or the like of the vehicle) of thevehicle from the user and stores the use reservation in the usereservation DB 110 b. Among data stored in the use reservation DB 110 b,information relating to a vehicle actually used by the user is stored inthe use history DB 110 b 1.

The acquisition unit 102 acquires an environmental parameter includingweather information, time information, map information, trafficinformation (traffic condition of a road, such as congestion), and thelike of a predetermined area and stores the environmental parameter inthe environmental parameter DB 110 a. Information stored in theenvironmental parameter DB 110 a and the use history stored in theabove-described use history DB 110 b 1 are stored in the storage unit110 in association with each other.

The prediction unit 103 performs a demand prediction of a vehicle to beused by the user based on correspondence information with informationstored in the environmental parameter DB 110 a and the use historystored in the use history DB 110 b 1 stored in association with eachother. The prediction unit 103 predicts, for example, the number ofdemanded vehicles in a specific area (specific station), a vehiclehaving a vehicle type or a color in great demand, and a vehicle mountedwith an accessory in great demand based on the above-describedcorrespondence information. Details of the correspondence informationwill be described below referring to FIG. 8.

The vehicle arrangement plan output unit 104 outputs an arrangement planof vehicles based on the demand prediction of the vehicle of theprediction unit 103. For example, as a result of the demand predictionof the prediction unit 103, an arrangement plan for arranging, at aspecific station where the number of demanded vehicles is large, morevehicles than other stations is output. For example, as a result of thedemand prediction of the prediction unit 103, an arrangement plan forarranging, at a specific station where a vehicle having a specificvehicle type, a specific color, or a specific accessory mounted thereinis in great demand, more vehicles having the vehicle type, the color, orthe accessory is output. A specific example of the vehicle arrangementplan will be described below referring to FIGS. 9 and 10.

The traveling route decision unit 105 decides a traveling route alongwhich the vehicle 30 should travel. In the embodiment, the travelingroute decision unit 105 decides a traveling route from a location wherethe usable vehicle 30 among the vehicles 30 registered in the carsharing system 1 is stored toward an arrangement location of a vehicleoutput from the vehicle arrangement plan output unit 104. When theusable vehicle 30 is the autonomous driving vehicle 30, the informationprocessing apparatus 10 notifies the in-vehicle device 30 a of thevehicle 30 of the traveling route decided by the traveling routedecision unit 105. The autonomous driving vehicle 30 receiving thenotification is controlled to the arrangement location of the vehicleoutput from the vehicle arrangement plan output unit 104 depending onthe decided traveling route. In this way, the information processingapparatus 10 in the embodiment may include a notification function(notification unit) of giving notification to the in-vehicle device 30 aof the vehicle 30. The information processing apparatus 10 may include acontrol function (controller) of performing control such that thein-vehicle device 30 a allows the autonomous driving vehicle 30receiving the notification to be autonomously driven to the arrangementlocation of the vehicle output from the vehicle arrangement plan outputunit 104.

The traveling route decision unit 105 is not limited as deciding thetraveling route from the storage location of the vehicle 30 registeredin the car sharing system 1 to the arrangement location of the vehicleoutput from the vehicle arrangement plan output unit 104. For example,when the user uses so-called one-way car sharing in which a vehiclerented from a specific station is returned to another station, thetraveling route decision unit 105 may decide a traveling route from areturn station set by the user (a destination set by the user) forreturning the vehicle to the arrangement location of the vehicle outputfrom the vehicle arrangement plan output unit 104. In addition, thedecision of the traveling route in the traveling route decision unit 105includes various aspects in which a traveling route from a predeterminedarea to an area different from the predetermined area is decided.

In the embodiment, a method of arranging the vehicle at the arrangementlocation of the vehicle output from the vehicle arrangement plan outputunit 104 is not limited as controlling and arranging the autonomousdriving vehicle 30. For example, a specific driver (for example, anowner, a salesperson, or the like) may drive the vehicle 30 and mayarrange the vehicle 30 at the arrangement location of the vehicle outputfrom the vehicle arrangement plan output unit 104.

Subsequently, specific examples of the environmental parameter DB 110 a,the use reservation DB 110 b, and the vehicle information DB 110 c willbe described.

FIG. 3 is a table showing an example of the environmental parameter DB110 a. In “date” and “time”, previous schedule and time registered inadvance in the car sharing system 1 are stored. In “location”, anylocation registered in advance in the car sharing system 1 is stored. In“weather”, weather information of a predetermined area is storedcorresponding to date and time. In regards to “date”, “time”, and“location”, for example, an owner who owns a predetermined number ofvehicles may set the period and the area in advance. The owner may set,for example, such that weather information around an area where a carsharing system business is scheduled to start is stored in theenvironmental parameter DB 110 a, or weather information of all areas inthe country may be stored in the environmental parameter DB 110 a.

FIG. 4 is a table showing an example of the use reservation DB 110 b.Information actually used by the user in the use reservation DB 110 b isstored in the use history DB 110 b 1.

In “user ID” shown in FIG. 4, an identifier for uniquely identifying theuser in the car sharing system 1 is stored. In “vehicle type”, “color”,and “accessory”, the type (for example, the vehicle type, color,accessory, or the like of the vehicle) of a vehicle that the userreserves use, the color of the vehicle, and various devices (forexample, including a navigation device, a seat for children, and anydevices mountable in the vehicle) mounted in the vehicle are stored.

In “various kinds of information” shown in FIG. 4, while any informationof a use reservation of the user can be stored, a use period of thevehicle to be used by the user is stored. Furthermore, in “various kindsof information”, for example, a use method of car sharing designated bythe user is stored. Specifically, designation of any one of theround-trip car sharing and the one-way car sharing is stored. In“getting-in point” of “getting-in place”, information (address, latitudeand longitude, or the like) indicating a point where the user desires toget in the vehicle 30 is stored. In “departure date and time” of“getting-in place”, date and time on which the user desires to departfrom the getting-in point” is stored. In “return date and time” of“getting-in place”, date and time on which the user who desires theround-trip car sharing desires to finally return to the getting-in placeis stored. In a case of a user who desires the one-way car sharing, noneis set in “return date and time” of “getting-in place”. In “getting-offpoint” of “getting-off place”, information (address, latitude andlongitude, or the like) indicating a point where the user desires to getoff the vehicle 30 is stored. In “departure date and time” of“getting-off place”, date and time on which the user who desires theround-trip car sharing desires to get in the vehicle 30 and depart fromthe getting-off place is stored.

In the example of FIG. 4, a user having a user ID “U01” uses the one-waycar sharing, and registers a use reservation for getting in the vehicle30 at home on January 15 and getting off the vehicle 30 at a store M. Auser having a user ID “U02” uses the round-trip car sharing, andregisters a use reservation for getting in the vehicle 30 at home onJanuary 15, 10:00, getting off the vehicle 30 at the store M, departingfrom the store M on January 15, 14:00, and returning home on January 15,17:00.

In “departure date and time”, the whole or a part of the date and thetime may be omitted when the user desires. For example, this means thatthe user U01 does not particularly desire the time of departure fromhome on January 15 (may depart from home at any time).

FIG. 5 is a table showing an example of the vehicle information DB 110c. In “vehicle ID”, an identifier for uniquely identifying the vehicle30 in the car sharing system 1 is stored. The vehicle ID may be, forexample, a license number of the vehicle 30. In “vehicle type”, avehicle type or a manufacturer name of the vehicle 30 is stored. In“capacity”, a seating capacity of the vehicle 30 is stored. In“availability information”, information indicating whether the vehicle30 is usable or in use is stored. In “storage location”, informationindicating a location where the vehicle 30 is stopped is stored. Sincethe storage location is also a location (a location capable ofgetting-in) where a user who holds a role of a driver can get in thevehicle 30, the storage location may be called a station where thevehicle 30 is rented.

Processing Procedure

Subsequently, a processing procedure that is executed by the informationprocessing apparatus 10 will be described. FIG. 6 is a flowchart showingan example of a processing procedure that is executed by the informationprocessing apparatus 10. Note that processing of Steps S101 and S102described below may be omitted when a state in which predetermined datais stored in a database (storage unit 110) in advance is premised.

In Step S101, the acquisition unit 102 stores weather information andthe like (including weather, location, time, and the like) correspondingto date and time, and a location in a predetermined period in theenvironmental parameter DB 110 a. While the acquisition unit 102receives an input from an owner who desires an output of an arrangementplan of vehicles, for example, and stores the above-described weatherinformation and the like in the environmental parameter DB 110 a, theacquisition unit 102 may store weather information and the like of apredetermined area in a previous entire period in the environmentalparameter DB 110 a regardless of an input from the owner.

In Step S102, the reception unit 101 receives a use reservation for carsharing from the user who desires to use car sharing and stores the usereservation in the use reservation DB 110 b. Among data stored in theuse reservation DB 110 b, history information actually used by the useris stored in the use history DB 110 b 1. In receiving the usereservation, the reception unit 101 may display a screen for receiving ause reservation in the user terminal 20 of the user who desires the usereservation. While the user can use car sharing in various aspects, forexample, the user inputs designation of any one of the round-trip carsharing and the one-way car sharing, a getting-in point, a time ofdeparture from a getting-in place, a getting-off point, a time ofdeparture from the getting-off point, and the like on the screen,thereby registering a desired use reservation in the informationprocessing apparatus 10.

In Step S103, the prediction unit 103 performs a demand prediction of avehicle to be used by the user based on correspondence information withthe environmental parameter (including at least weather information andtime information in a predetermined area) stored in the environmentalparameter DB 110 a and the use history of the user stored in the usehistory DB 110 b 1 stored in association with each other. Hereinafter,demand prediction processing that is executed by the prediction unit 103will be described. FIG. 7 is a flowchart showing an example of thedemand prediction processing shown in FIG. 6.

First, as shown in Step S1031 of FIG. 7, the correspondence informationwith the above-described environmental parameter and the use history ofthe user stored in association with each other is generated. An exampleof the correspondence information is shown in FIG. 8.

Next, as shown in Steps S1032 and S1033 of FIG. 7, the prediction unit103 compares and analyzes the environmental parameter and the usehistory of the user based on the correspondence information and extractsthe type of a vehicle used by the user in a specific time period foreach specific area.

For example, the following information can be extracted based on thecorrespondence information of FIG. 8. In detail, information that usershaving user IDs “U01”, “U02”, “U03” use the vehicle 30 having a vehicletype “XXX” as the type of the vehicle 30 in A-Ku, Tokyo in a use timeperiod (a time period during weather is cloudy) of, for example, 10:00to 11:00 of the use time of each user can be extracted. For the use time(10:00 to 11:00), the color of the vehicle 30 used by each user isdifferent, the color of the vehicle 30 used by the user having the userID “U01” is white, the color of the vehicle 30 used by the user havingthe user ID “U02” is black, and the color of the vehicle 30 used by theuser having the user ID “U03” is dark blue.

As shown in Step S1034 of FIG. 7, the prediction unit 103 predictsdemand for each type of vehicle based on the type of the vehicle (thevehicle type, color, accessory, and the like of the vehicle 30 used bythe user) extracted in Step S1033 and the environmental parameter. Forexample, the prediction unit 103 can perform a demand prediction thatdemand for the vehicle 30 having the vehicle type “XXX” in the timeperiod (the time period during which weather is cloudy) of 10:00 to11:00 of an area in A-Ku, Tokyo shown in FIG. 8 is greater than otherareas, demand for the vehicle 30 in the same time period of an area inB-Shi, Kanagawa-Ken is small, and the like. For example, the predictionunit 103 can perform a demand prediction that there is demand for thevehicle 30 having the vehicle type “XXX” in a time period (a time periodduring which weather is fine) of 16:00 to 17:00 of the area in B-Shi,Kanagawa-Ken, demand for the vehicle 30 having the vehicle type “XXX” ofthe area in B-Shi, Kanagawa-Ken is relatively smaller than demand forthe vehicle 30 having the vehicle type “XXX” in the time period of 10:00to 11:00 of the area in A-Ku, Tokyo, and the like.

In Step S104 subsequent to Step S103 of FIG. 6, the vehicle arrangementplan output unit 104 outputs the arrangement plan of the vehicles 30based on the demand prediction of the vehicle 30 of the prediction unit103. FIG. 9 shows an example of the arrangement plan of the vehicles 30output from the vehicle arrangement plan output unit 104.

FIG. 9 is a diagram showing an example of arrangement of vehicles outputfrom the vehicle arrangement plan output unit 104 based on the demandprediction of the vehicle 30 of the prediction unit 103. In the exampleof the vehicle arrangement shown in FIG. 9, a situation in which apredetermined number of vehicles having different vehicle types (twovehicle types) are arranged based on a demand prediction of vehicles infour different areas is assumed.

In the example shown in the drawing, as a result of the demandprediction of the prediction unit 103, a different number of vehiclesare arranged according to an area where the number of demand predictedvehicles is great (that is, an area where the vehicle is in greatdemand). Specifically, an example where the number of demand predictedvehicles 30B in A-Ku, Tokyo is five (the number of vehicles 30B having avehicle type B is five), the number of demand predicted vehicles inC-Ku, Tokyo is five (the number of vehicles 30A having a vehicle type Ais two, and the number of vehicles 30B having the vehicle type B isthree), the number of demand predicted vehicles in B-Ku, Yokohama-Shi,Kanagawa-Ken is two (the number of vehicles 30A having the vehicle typeA is two), and the number of demand predicted vehicles in B-Ku, Tokyo isone (the number of vehicles 30A having the vehicle type A is one) isshown.

From a viewpoint of the number of demand predicted vehicles by vehicletype in the drawing, the number of demand predicted vehicles 30B havingthe vehicle type B is greatest in A-Ku, Tokyo, is second greatest inC-Ku, Tokyo, and is smallest in B-Ku, Tokyo and B-Ku, Yokohama-Shi,Kanagawa-Ken. The number of demand predicted vehicles 30A having thevehicle type A is greatest in C-Ku, Tokyo and B-Ku, Yokohama-Shi,Kanagawa-Ken, is second greatest in B-Ku, Tokyo, and is smallest inA-Ku, Tokyo. In this way, the arrangement plan of the vehicles (thearrangement locations of the vehicles and the number of vehicles) isoutput based on the demand prediction predicted by vehicle type for eacharea.

In FIG. 9, although, as an example of the vehicle arrangement planoutput from the vehicle arrangement plan output unit 104, an examplewhere a predetermined number of vehicles having different vehicle typesare arranged has been shown, the disclosure is not limited thereto, anda predetermined number of vehicles may be arranged according to thecolor of the vehicle in great demand in each area. FIG. 10 shows anexample where vehicles having different colors are arranged in fourdifferent areas based on the demand prediction of the prediction unit103, respectively. In the example shown in FIG. 10, the vehicles havingthe same vehicle type are arranged in all areas.

In the example of the vehicle arrangement plan output from the vehiclearrangement plan output unit 104 shown in FIG. 10, vehicles are arrangedin each area based on a prediction of the prediction unit 103 for avehicle having a color in great demand as follows. That is, three greyvehicles 30A2 and two white vehicles 30A1 are arranged in A-Ku, Tokyo,one black vehicle 30A3 is arranged in B-Ku, Tokyo, one black vehicle30A3, one grey vehicle 30A2, and one white vehicle 30A1 are arranged inC-Ku, Tokyo, and one black vehicle 30A3 and one white vehicle 30A1 arearranged in B-Ku, Yokohama-Shi, Kanagawa-Ken.

As shown in FIGS. 9 and 10, the prediction unit 103 predicts the levelof demand for the vehicle type or color of the vehicle for each area,and the vehicle arrangement plan output unit 104 outputs an arrangementplan of vehicles according to the prediction of demand. Although FIGS. 9and 10 show examples of a case where vehicles having different vehicletypes are arranged and a case where vehicles having different colors arearranged, respectively, the vehicle arrangement plan output unit 104 mayoutput arrangement of vehicles in which vehicle types and colors arecombined.

In addition to the examples shown in FIGS. 9 and 10, the prediction unit103 may predict demand for an accessory of a vehicle for each area, andthe vehicle arrangement plan output unit 104 may output arrangement ofvehicles based on the prediction. In addition, demand for each area canbe predicted based on a history previously used by the user, and thevehicle arrangement plan output unit 104 can output a vehiclearrangement plan in various forms based on the demand prediction.

As described above, the prediction unit 103 performs the demandprediction of the vehicle information (including a color, a vehicletype, an accessory, and the like of the vehicle) used by the user foreach predetermined area, and the vehicle arrangement plan output unit104 outputs the arrangement location of the vehicle corresponding to thevehicle information, the number of vehicles, and the like based on thedemand prediction of the vehicle information for each predeterminedarea.

In the embodiment described above, the acquisition unit 102 may furtheracquire a road situation or a degree of congestion of a road (includinga traffic situation of a road, or the like) in a predetermined area, andthe vehicle arrangement plan output unit 104 may output an arrangementplan of vehicles based on the demand prediction of the vehicle of theprediction unit 103 and the degree of congestion of the road.

According to the embodiment described above, the prediction unit 103performs a demand prediction based on the above-described environmentalparameter and the use history of the user, and the vehicle arrangementplan output unit 104 outputs the arrangement plan of the vehicles basedon a prediction result. Since the demand prediction is, for example, aprediction in consideration of parameters including an area where thereare many use reservations for a vehicle of the users, a time period ofcongestion, weather information, and the like, it is possible to copewith a situation in which the degree of uneven distribution increasesbefore the degree of uneven distribution actually increases compared toa configuration in which processing for decreasing the degree of unevendistribution in a stopgap manner according to the current degree ofuneven distribution of vehicles is executed. That is, since the ownercan ascertain a time period during which a vehicle is shared, a locationwhere a vehicle is shared, weather when a vehicle is shared, a type ofvehicle to be shared, it is possible to improve availability of vehiclesowned by the owner. As a result, it is possible to provide a car sharingsystem capable of renting vehicles to more users.

The above-described embodiment is for facilitating the understanding ofthe disclosure and is not to be interpreted to limit the disclosure. Theflowchart described in the embodiment, a sequence, elements in theembodiment, and arrangement, material, condition, shape, size, and thelike of each of the elements are not limited to those described aboveand can be appropriately modified. In addition, components described indifferent embodiments can be partially substituted with each other orcan be combined with each other.

What is claimed is:
 1. A non-transitory computer-readable recordingmedium storing an information processing program causing a computer toexecute: acquiring at least one of weather information and timeinformation as an environmental parameter, acquiring a use historyincluding a use section, a use time, and vehicle information of avehicle previously used by a user, performing a demand prediction of avehicle to be used by the user based on correspondence information withthe weather information and the time information and the use historystored in association with each other, outputting a plan of arrangementlocations of the vehicles planed based on the demand prediction of thevehicle; receiving a use reservation of a vehicle; storing the usereservation in a use reservation database; deciding a traveling routefrom a location where a vehicle determined as being usable based on theuse reservation is parked, toward an arrangement location of thevehicle; notifying the vehicle determined as being usable based on theuse reservation, of the traveling route, the vehicle being an autonomousdriving vehicle; and controlling the notified vehicle to the arrangementlocation of the vehicle along the traveling route.
 2. Thecomputer-readable, non-transitory recording medium according to claim 1,wherein the vehicle information includes a color, a vehicle type, and anaccessory of the vehicle, and wherein the program causing the computerto: perform the demand prediction of the vehicle to be used by the userfor each predetermined area, the vehicle corresponding to the vehicleinformation; and output arrangement locations of vehicles correspondingto the vehicle information and the number of the vehicles for eachpredetermined area based on the demand prediction of the vehiclecorresponding to the vehicle information.
 3. The computer-readable,non-transitory recording medium according to claim 1, wherein theprogram causing the computer to: acquire a degree of congestion of aroad in a predetermined area; and output the plan of the arrangementlocations of the vehicles planed based on the demand prediction of thevehicle and the degree of congestion of the road.
 4. Thecomputer-readable, non-transitory recording medium according to claim 1,wherein the vehicle information includes a seating capacity of thevehicle.
 5. The computer-readable, non-transitory recording mediumaccording to claim 1, wherein the vehicle information includes anidentifier for uniquely identifying the vehicle.
 6. Thecomputer-readable, non-transitory recording medium according to claim 5wherein the identifier is a license number of the vehicle.
 7. A methodof information processing for a car sharing system, the methodcomprising: acquiring at least one of weather information and timeinformation as an environmental parameter, acquiring a use historyincluding a use section, a use time, and vehicle information of avehicle previously used by a user, performing a demand prediction of avehicle to be used by the user based on correspondence information withthe weather information and the time information and the use historystored in association with each other, outputting a plan of arrangementlocations of the vehicles planed based on the demand prediction of thevehicle; receiving a use reservation of a vehicle; storing the usereservation in a use reservation database; deciding a traveling routefrom a location where a vehicle determined as being usable based on theuse reservation is parked, toward an arrangement location of thevehicle; notifying the vehicle determined as being usable based on theuse reservation, of the traveling route, the vehicle being an autonomousdriving vehicle; and controlling the notified vehicle to the arrangementlocation of the vehicle along the traveling route.
 8. The methodaccording to claim 7, wherein the vehicle information includes a color,a vehicle type, and an accessory of the vehicle, and wherein the methodfurther comprises: performing the demand prediction of the vehicle to beused by the user for each predetermined area, the vehicle correspondingto the vehicle information; and outputting arrangement locations ofvehicles corresponding to the vehicle information and the number of thevehicles for each predetermined area based on the demand prediction ofthe vehicle corresponding to the vehicle information.
 9. The methodaccording to claim 7 further comprising: acquiring a degree ofcongestion of a road in a predetermined area; and outputting the plan ofthe arrangement locations of the vehicles planed based on the demandprediction of the vehicle and the degree of congestion of the road. 10.The method according to claim 7, wherein the vehicle informationincludes a seating capacity of the vehicle.
 11. The method according toclaim 7, wherein the vehicle information includes an identifier foruniquely identifying the vehicle.
 12. The method according to claim 11,wherein the identifier is a license number of the vehicle.
 13. A carsharing system comprising: a plurality of vehicles; and an informationprocessing apparatus comprising: an environmental parameter acquisitionunit configured to acquire at least one of weather information and timeinformation of a predetermined area as an environmental parameter; a usehistory unit configured to acquire a use history including a usesection, a use time, and vehicle information of a vehicle of theplurality of vehicles being previously used by a user; a demandprediction unit configured to perform a demand prediction of a vehicleof the plurality of vehicles to be used by the user based oncorrespondence information with the environmental parameter and the usehistory stored in association with each other; a vehicle arrangementplan output unit configured to output a plan of arrangement locations ofthe vehicles planed based on the demand prediction of the vehicleperformed by the demand prediction unit; a reception unit configured toreceive a use reservation of a vehicle of the plurality of vehicles andstore the use reservation in a use reservation database; a travelingroute decision unit configured to decide a traveling route from alocation where a vehicle of the plurality of vehicles determined asbeing usable based on the use reservation is parked, toward anarrangement location of the vehicle output from the vehicle arrangementplan output unit; a notification unit configured to notify the vehicledetermined as being usable based on the use reservation, of thetraveling route decided by the traveling route decision unit, thevehicle being an autonomous driving vehicle; and a controller configuredto control the vehicle notified by the notification unit, to thearrangement location of the vehicle output from the vehicle arrangementplan output unit along the traveling route.
 14. The car sharing systemaccording to claim 13, wherein: the vehicle information includes acolor, a vehicle type, and an accessory of the vehicle; the demandprediction unit is configured to perform the demand prediction of thevehicle to be used by the user for each predetermined area, the vehiclecorresponding to the vehicle information; and the vehicle arrangementplan output unit is configured to output arrangement locations ofvehicles corresponding to the vehicle information and the number of thevehicles for each predetermined area based on the demand prediction ofthe vehicle corresponding to the vehicle information.
 15. The carsharing system according to claim 13, wherein: the environmentalparameter acquisition unit is configured to further acquire a degree ofcongestion of a road in a predetermined area; and the vehiclearrangement plan output unit is configured to output the plan of thearrangement locations of the vehicles planed based on the demandprediction of the vehicle performed by the demand prediction unit andthe degree of congestion of the road.
 16. The car sharing systemaccording to claim 13, wherein the vehicle information includes aseating capacity of the vehicle.
 17. The car sharing system according toclaim 13, wherein the vehicle information includes an identifier foruniquely identifying the vehicle.
 18. The car sharing system accordingto claim 17, wherein the identifier is a license number of the vehicle.